Blue-noise remeshing with farthest point optimization

D.M. Yan, J. Guo, X. Jia, X. Zhang, P. Wonka
Computer Graphics Forum, volume 33, issue 5, pp. 167-176, (2014)

Blue-noise remeshing with farthest point optimization


Blue-noise sampling, Remeshing


​In this paper, we present a novel method for surface sampling and remeshing with good blue-noise properties. Our approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality blue-noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue-noise properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior to the current state-of-theߚart approaches.


DOI: 10.1111/cgf.12442


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